07: Python_Functions_for_Time_Series_Analysis_3.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "Python_Functions_for_Time_Series_Analysis_01.ipynb",
      "provenance": [],
      "collapsed_sections": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "jh6JcRlqv5ac"
      },
      "source": [
        "In this notebook some very useful python functions are discussed in details, that will be very very useful in many time series probels..."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "6i7OnJ7RmfRc"
      },
      "source": [
        "import datetime\n",
        "import pandas as pd\n",
        "import requests\n",
        "import matplotlib as mpl\n",
        "import matplotlib.pyplot as plt\n",
        "\n",
        "mpl.rcParams['figure.figsize'] = (15, 15)\n",
        "mpl.rcParams['axes.grid'] = False"
      ],
      "execution_count": 1,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "iU10jK1y2u9H",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "56166e8d-14dd-47d6-9751-65f94ba32104"
      },
      "source": [
        "coindeskURL = 'https://api.coindesk.com/v1/bpi/historical/close.json?'\n",
        "\n",
        "start = datetime.date(2017, 1 ,1)\n",
        "#end = datetime.date(2020, 7, 2)\n",
        "end = datetime.datetime.now().date()\n",
        "url = f'{coindeskURL}start={start:%Y-%m-%d}&end={end:%Y-%m-%d}'\n",
        "\n",
        "result = requests.get(url)\n",
        "result.content"
      ],
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              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data was produced from the CoinDesk Bitcoin Price Index. BPI value data returned as USD.\",\"time\":{\"updated\":\"Dec 26, 2020 15:50:29 UTC\",\"updatedISO\":\"2020-12-26T15:50:29+00:00\"}}'"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 2
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "6T8tWXBimgvi",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 450
        },
        "outputId": "21c6e91d-e3df-46f6-b401-46d2a1c4ec15"
      },
      "source": [
        "data = pd.read_json(result.content).iloc[:-2,:1]\n",
        "data.index.name = 'date'\n",
        "data.index = pd.to_datetime(data.index)\n",
        "data"
      ],
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>bpi</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>date</th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2017-01-01</th>\n",
              "      <td>997.6888</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-01-02</th>\n",
              "      <td>1018.0500</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-01-03</th>\n",
              "      <td>1030.8175</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-01-04</th>\n",
              "      <td>1129.8700</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-01-05</th>\n",
              "      <td>1005.8150</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-12-21</th>\n",
              "      <td>22718.2250</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-12-22</th>\n",
              "      <td>23817.3067</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-12-23</th>\n",
              "      <td>23229.0133</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-12-24</th>\n",
              "      <td>23729.6483</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-12-25</th>\n",
              "      <td>24707.8017</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>1455 rows × 1 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "                   bpi\n",
              "date                  \n",
              "2017-01-01    997.6888\n",
              "2017-01-02   1018.0500\n",
              "2017-01-03   1030.8175\n",
              "2017-01-04   1129.8700\n",
              "2017-01-05   1005.8150\n",
              "...                ...\n",
              "2020-12-21  22718.2250\n",
              "2020-12-22  23817.3067\n",
              "2020-12-23  23229.0133\n",
              "2020-12-24  23729.6483\n",
              "2020-12-25  24707.8017\n",
              "\n",
              "[1455 rows x 1 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 3
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "yjroYrCSolpZ",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 308
        },
        "outputId": "96c1b1b1-8e5a-4b10-84e0-7c110d84d197"
      },
      "source": [
        "data.plot()"
      ],
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f2ad25d3f60>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 4
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "_4iF3UvsvrRy"
      },
      "source": [
        "D\tCalendar day\t\n",
        "\n",
        "B\tBusiness day\n",
        "\n",
        "W\tWeekly\t\t\n",
        "\n",
        "M\tMonth\n",
        "\n",
        "Q\tQuarter\n",
        "\n",
        "A\tYear end\n",
        "\n",
        "H\tHours\n",
        "\n",
        "T\tMinutes\t\t\n",
        "\n",
        "S\tSeconds\t\t\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "TfXo3HpwTwT7",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 576
        },
        "outputId": "7687b330-d542-4fb4-d63e-18480258be2f"
      },
      "source": [
        "data.resample('Q').mean()"
      ],
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>bpi</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>date</th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2017-03-31</th>\n",
              "      <td>1034.169242</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-06-30</th>\n",
              "      <td>1919.658520</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-09-30</th>\n",
              "      <td>3506.611449</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-12-31</th>\n",
              "      <td>9413.347972</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018-03-31</th>\n",
              "      <td>10468.423818</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018-06-30</th>\n",
              "      <td>7747.165877</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018-09-30</th>\n",
              "      <td>6798.307918</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018-12-31</th>\n",
              "      <td>5169.904503</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2019-03-31</th>\n",
              "      <td>3781.639959</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2019-06-30</th>\n",
              "      <td>7295.205002</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2019-09-30</th>\n",
              "      <td>10369.583753</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2019-12-31</th>\n",
              "      <td>7994.267917</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-03-31</th>\n",
              "      <td>8273.003262</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-06-30</th>\n",
              "      <td>8649.343719</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-09-30</th>\n",
              "      <td>10613.818097</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-12-31</th>\n",
              "      <td>16106.969853</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                     bpi\n",
              "date                    \n",
              "2017-03-31   1034.169242\n",
              "2017-06-30   1919.658520\n",
              "2017-09-30   3506.611449\n",
              "2017-12-31   9413.347972\n",
              "2018-03-31  10468.423818\n",
              "2018-06-30   7747.165877\n",
              "2018-09-30   6798.307918\n",
              "2018-12-31   5169.904503\n",
              "2019-03-31   3781.639959\n",
              "2019-06-30   7295.205002\n",
              "2019-09-30  10369.583753\n",
              "2019-12-31   7994.267917\n",
              "2020-03-31   8273.003262\n",
              "2020-06-30   8649.343719\n",
              "2020-09-30  10613.818097\n",
              "2020-12-31  16106.969853"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 5
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "G2iqTbGyeylx",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 296
        },
        "outputId": "e28c600a-5681-4f14-a2a7-3c244de93f02"
      },
      "source": [
        "data.resample('Q').mean().plot()"
      ],
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f2ad11c1668>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 6
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Ko8OCen2G6Io",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 582
        },
        "outputId": "56ef4d4f-14fd-42bf-ada7-6c6dd009d7ae"
      },
      "source": [
        "data.plot()\n",
        "data.resample('M').mean().plot()"
      ],
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f2ad0c06748>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 7
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "HBBADRvKqFue",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 235
        },
        "outputId": "130b5b8f-53d9-42f3-cd94-4b5dbf6142c2"
      },
      "source": [
        "data[:5]"
      ],
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>bpi</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>date</th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2017-01-01</th>\n",
              "      <td>997.6888</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-01-02</th>\n",
              "      <td>1018.0500</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-01-03</th>\n",
              "      <td>1030.8175</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-01-04</th>\n",
              "      <td>1129.8700</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-01-05</th>\n",
              "      <td>1005.8150</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                  bpi\n",
              "date                 \n",
              "2017-01-01   997.6888\n",
              "2017-01-02  1018.0500\n",
              "2017-01-03  1030.8175\n",
              "2017-01-04  1129.8700\n",
              "2017-01-05  1005.8150"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "RMWHU64vv5mH",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 235
        },
        "outputId": "1d990b35-870e-4a38-b73a-129ce8d2606e"
      },
      "source": [
        "data[:5].diff()"
      ],
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>bpi</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>date</th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2017-01-01</th>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-01-02</th>\n",
              "      <td>20.3612</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-01-03</th>\n",
              "      <td>12.7675</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-01-04</th>\n",
              "      <td>99.0525</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-01-05</th>\n",
              "      <td>-124.0550</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                 bpi\n",
              "date                \n",
              "2017-01-01       NaN\n",
              "2017-01-02   20.3612\n",
              "2017-01-03   12.7675\n",
              "2017-01-04   99.0525\n",
              "2017-01-05 -124.0550"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "i6SpGO9jylw4",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 235
        },
        "outputId": "4496ae99-e2d5-48b4-bff2-5b3bd2c9fec7"
      },
      "source": [
        "data[:5].diff(2)"
      ],
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>bpi</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>date</th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2017-01-01</th>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-01-02</th>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-01-03</th>\n",
              "      <td>33.1287</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-01-04</th>\n",
              "      <td>111.8200</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-01-05</th>\n",
              "      <td>-25.0025</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                 bpi\n",
              "date                \n",
              "2017-01-01       NaN\n",
              "2017-01-02       NaN\n",
              "2017-01-03   33.1287\n",
              "2017-01-04  111.8200\n",
              "2017-01-05  -25.0025"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "hW774IQ4Lik3",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 308
        },
        "outputId": "02184159-81b0-4669-de6f-3f96084c4627"
      },
      "source": [
        "pd.concat([data['bpi'], data['bpi'].diff(2), data['bpi'].diff()],axis=1).plot()"
      ],
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f2ad0c06198>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 11
        },
        {
          "output_type": "display_data",
          "data": {
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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "LnDeDaj4Sj4i",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 235
        },
        "outputId": "81ead83f-0b6b-4dee-aa70-22767b0692ef"
      },
      "source": [
        "data[:5]"
      ],
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>bpi</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>date</th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2017-01-01</th>\n",
              "      <td>997.6888</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-01-02</th>\n",
              "      <td>1018.0500</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-01-03</th>\n",
              "      <td>1030.8175</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-01-04</th>\n",
              "      <td>1129.8700</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-01-05</th>\n",
              "      <td>1005.8150</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                  bpi\n",
              "date                 \n",
              "2017-01-01   997.6888\n",
              "2017-01-02  1018.0500\n",
              "2017-01-03  1030.8175\n",
              "2017-01-04  1129.8700\n",
              "2017-01-05  1005.8150"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 12
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "R_tMy4HULiY7",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 235
        },
        "outputId": "72eea830-e299-4f85-89e4-1cb23b5ace5a"
      },
      "source": [
        "data[:5].shift()"
      ],
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
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              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>bpi</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>date</th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2017-01-01</th>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-01-02</th>\n",
              "      <td>997.6888</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-01-03</th>\n",
              "      <td>1018.0500</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-01-04</th>\n",
              "      <td>1030.8175</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-01-05</th>\n",
              "      <td>1129.8700</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                  bpi\n",
              "date                 \n",
              "2017-01-01        NaN\n",
              "2017-01-02   997.6888\n",
              "2017-01-03  1018.0500\n",
              "2017-01-04  1030.8175\n",
              "2017-01-05  1129.8700"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 13
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "h7lz03Bzg29W",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 289
        },
        "outputId": "23ea4b69-ee4c-4254-92bb-a273ce113b74"
      },
      "source": [
        "data[:5].tshift(2)"
      ],
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.6/dist-packages/ipykernel_launcher.py:1: FutureWarning: tshift is deprecated and will be removed in a future version. Please use shift instead.\n",
            "  \"\"\"Entry point for launching an IPython kernel.\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "execute_result",
          "data": {
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              "    .dataframe tbody tr th:only-of-type {\n",
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              "    <tr>\n",
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              "      <th></th>\n",
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              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2017-01-03</th>\n",
              "      <td>997.6888</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-01-04</th>\n",
              "      <td>1018.0500</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-01-05</th>\n",
              "      <td>1030.8175</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-01-06</th>\n",
              "      <td>1129.8700</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-01-07</th>\n",
              "      <td>1005.8150</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                  bpi\n",
              "date                 \n",
              "2017-01-03   997.6888\n",
              "2017-01-04  1018.0500\n",
              "2017-01-05  1030.8175\n",
              "2017-01-06  1129.8700\n",
              "2017-01-07  1005.8150"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 14
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "xraQJjYyKTh0",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 235
        },
        "outputId": "95b09089-6d86-41cb-f72a-ff244083d11d"
      },
      "source": [
        "data[:5] - data[:5].shift()"
      ],
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>bpi</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>date</th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2017-01-01</th>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-01-02</th>\n",
              "      <td>20.3612</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-01-03</th>\n",
              "      <td>12.7675</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-01-04</th>\n",
              "      <td>99.0525</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-01-05</th>\n",
              "      <td>-124.0550</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                 bpi\n",
              "date                \n",
              "2017-01-01       NaN\n",
              "2017-01-02   20.3612\n",
              "2017-01-03   12.7675\n",
              "2017-01-04   99.0525\n",
              "2017-01-05 -124.0550"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 15
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "u5V7Z3UXP_yT",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 235
        },
        "outputId": "521aa4ed-066d-42b6-80c5-8b61a9182a60"
      },
      "source": [
        "data[:5] - data[:5].shift(2)"
      ],
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>bpi</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>date</th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2017-01-01</th>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-01-02</th>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-01-03</th>\n",
              "      <td>33.1287</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-01-04</th>\n",
              "      <td>111.8200</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-01-05</th>\n",
              "      <td>-25.0025</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                 bpi\n",
              "date                \n",
              "2017-01-01       NaN\n",
              "2017-01-02       NaN\n",
              "2017-01-03   33.1287\n",
              "2017-01-04  111.8200\n",
              "2017-01-05  -25.0025"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 16
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "6OFuj6T_y2sk",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 350
        },
        "outputId": "a86ffea1-12b1-4737-a1d2-7c76710faa69"
      },
      "source": [
        "pd.concat([data,data-data.shift(), data.tshift(365)],axis=1).plot()"
      ],
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.6/dist-packages/ipykernel_launcher.py:1: FutureWarning: tshift is deprecated and will be removed in a future version. Please use shift instead.\n",
            "  \"\"\"Entry point for launching an IPython kernel.\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f2ad098d5c0>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 17
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "S06X4MbC8XFq",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 308
        },
        "outputId": "51f87d72-1787-4140-f845-3e77e6d55014"
      },
      "source": [
        "data.rolling(window=10).mean().plot()"
      ],
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f2ad0851278>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 18
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "D26aPKkY_bhZ",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 296
        },
        "outputId": "a6593099-465a-4480-d19b-a7a4f063530c"
      },
      "source": [
        "data.resample('W').mean().rolling(window=10).mean().plot()"
      ],
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f2ad121e438>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 19
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "2jcFQKPh_7gC",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 582
        },
        "outputId": "2493c5c6-b57a-45bb-8429-c2401213df10"
      },
      "source": [
        "data.rolling(window=50).mean().plot()\n",
        "data.rolling(window=50, win_type='gaussian').sum(std=10).plot()"
      ],
      "execution_count": 20,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f2ac190e2b0>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 20
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "t8biAFc3AcRv",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 311
        },
        "outputId": "7352fe73-b879-43f7-b028-7903e3100ed6"
      },
      "source": [
        "data.ewm(span=50).mean().plot()"
      ],
      "execution_count": 21,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f2ad1227320>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 21
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "TU4KDA5dQxXS",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 308
        },
        "outputId": "216501bb-6760-4327-9146-a86a76c0f97e"
      },
      "source": [
        "pd.concat([data,data.rolling(window=100).mean(), data.ewm(span=100).mean()],axis=1).plot()"
      ],
      "execution_count": 22,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f2ac14f14e0>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 22
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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As+hJto15Gw8HchVFMbuNS+oQgUDrJAzySkyOx1IzkEgaHwLv/Y7XJK2hX0Q//M/sgphBXufVVBh8CHQE+gGpwNs1XKdaCCHuEkJsF0Jsz8jIOB8v2SS5sEsEOq3nD8+Liw+c591IJJJzRXiRBSfyTpCQm8CEthdAxhFoW8vCQFGUs4qiWBRFsQKfopqBAFKAWKepMbYxb+NZQAshhI/buLfX/URRlEGKogyKiIioydabNWGBvgyJC2Ncj9YuPgNntpyoqkVQIpE0FC7pGeVxfFWi2tBqnK4VoEDMQK9r1EgYCCGinZ5eCdgjjRYBNwgh/IQQ8UBn4B9gG9DZFjnki+pkXqSoGU5rgGts588AFtZkT5LKsSoK3aKDAVx8BgAa71qmRCJpoIQH+jJ9aDvCAj0HYf5x6g/6R/andWaCOtBmgNe1qhJa+iOwGegqhEgWQtwOvCmE2CeE2AtcBDwMoCjKAWA+cBBYAcy0aRBm4H5gJXAImG+bC/Ak8IgQIgHVh/B5ZXuS1AyrVUFj0ycLSk2ux2TisUTS6DBZrOi8hJQm5iVyNOco49uPh+QdENYRArw7kCtte6koyjQPw16/sBVFeRV41cP4MmCZh/ETlJmZJHWIouAkDFz7HneMCOR4RlF9bEsikdQQs1Upp+XbWXVKNRGNbzcOlr0MHcZUuJbsgdyMsCqKwxwk3DxOPdqEcjbfQI82IfWwM4lEUhPMFsVrstmqU6voE9GHKIsFCs9W6DwGWY6iWWFRFDQ2aWByq0Gk0wgKDWb+OZnN6kNn62N7EomkGlisCiar1WNkYFJ+EoeyDzGh/QRI2qoOVuA8BikMmhVWJzNROWHgdHexxykJTSKRNExOZBSiKBAXHlju2LqUdQCMbTcWTqwFv1CI6lvhelIYNCMUJzORuzBwthppvQUtSySSBkNavlp6PjYsoNyxf1L/ISYohpiA1nBkOXS8CLQVewWkMGhGOGsGU/u5JnrP21aWIO7jJSFNIpE0HG7+/B8AQvxdv+QtVgvbzm5jSPQQSPgTijKg7w2VrieFQTPCYi3TDIZ2CCfx9cke58kGNxJJw+brTYmOx8F619LVB7MOUmAsYHDUYNj9PQRGQKdxla4phUEzwWpLJHDPPPbkfNorfQYSSYNm9qKysjEhbk1tVp1ehY/wYXRYLziyAvpcD1rPvQ6ckcKgmWB2CAPXcU89U51LWkskkobLq1f2ctEMFEVhVeIqhrUZRuiRP8Bqgr6eUsXKI4VBM8GqeNYM/Hy0AMyd1t8xZpHpyBJJo+C6QbEuz4/lHiO5MFmNItrzA0T1hijv5a2dkcKgmeBNM7ALid5tQ/lwulq3RAoDiaThkppX4njsXopiY8pGAC7Qt4Ezu6qsFYAUBs0Gi8WzZmD/3tdpBZf2jmZkp3As0oEskTRYLvzPWgAeHd+l3LFtaduIC4kj8shKEFrofW2V15XCoJlg/4J3r2Nijxyy32FohJCaQRMnJbeEj/8+LqPGGiFGs9XRp/yqgTEux8xWM7vSdzG49UDYMw86j4egyCqvLYVBM8FsVT9AGjdhUOZLEI7fKbklHDgjI4qaKrd/tY3Xlh/mTF5pfW9FUk1OZanFJK/q35a2Lfxdjh3JPkKhqZBB6KEwDfrfVK21pTBoJthkQXnNwPbbnnWsFYKMAgOT5244j7uTnE/yS0yVT5I0SHKK1ffuajetAGD72e0ADDq0CoKjofMl1VpbCoNmgl0zcC81cc0A9UPl76tGFWlll5smj90KKID9KXk89vMeaRpsJBjMati3n0/5r+5tadto7x9JZNJ2uOAx8PHc8MYbUhg0E+yagfuX/TOTunPopYnodTUUBtknwFBYG1uUnCfs/iOrojDji3/4ZUcy6QXSZNQYMJjUf2R7SLidEnMJW1O3MtyEWpSu743VXlsKg2aCQzNwb3epEQ6twP68SigK/PEczO0P/+kEWz6qtb1K6ha74/jZ3/c7EgxlouH55YEfd7F8X2q1zzPYnMd+Otev7s1nNlNqKeXilMNqHSLf8sXrKkMKg2aCu6PYG1WqWGoxwdJHYNNc6HklxI2CFU9B4sba2KqkjrFbhNYeyXCYh9w730nqDqtVYfGeM9z7/c5qn+vNTPTX6b8I1vgyqLgQBt5ao31JYdBMKEs6q0QYOB03u5W5BlRB8P01sP0LGDkLrvkSrvsagqNU4SBp8JjMZe+rr+1LxZNT2WC2cCa3pNy4pObklZhILzDU+HyHZuBkJjJbzfydvJYLikvQxY2G1j1qtLZse9lMsNRAGBgt1vIt9TbNVZtlTJlTdgfiGwh9roPN70NRJgS2qsWdS2obg5MwKDSoGoEnM9FNn21lW2IOCa9e6rW1oqR69H3xj3Jjn60/QYnRwgNjO1d6vsFUXjPYlraNXEMeF+dlwzUf1nhv8h1uJjiEQSVmIOfjdmeVg1ObYc1r0P3y8qpo32lgNcPuH2pju5I6xOhB4zuclu/y3GpV2JaYA8DJzKLzsq+mzubjWeXGFEXhlaWHeHvV0SqtkVeiCu8AvzLNYMnhnwiyWrkgegTEX1Dj/Ulh0ExwmIkqaVzj7EBetj+VjQmZarTQ32/Cd1dBi3ZwuQdzUGR3iBkM++bX6r4l54f//nnM5fmiPWccj+2x7ZJzY9qnW8qNxT+9zPHYo1nWjVPZRUSH6h1momJjEX8m/cX4EhP6KXNcWxZWEykMmgkJZ9Xwz+hQfYXznK0B/1qwn1c//wneGwBrXoVOY2HGYvBv6fnk7pdD2j7IOVVb25bUE6WmMrPRjlM59biTpkmgr7bcmN1k5wmLVeHvoxmcyCiinVOby9UbXqUYhcu7T4MWsV7PrwpSGDQTUnJLEAK6RAZXOE/BiMYvDW3gUfTaLD7yfRs0Orj9T7j+Owgta5c5d/Ux3lp5pOzkbrbOaUeWIWncBDr1uXhjxeF63EnTwbl3yE3D2pc7XlFE14//nGbGF/+wOymX9uE2YVCYwcKEBbRVtAy44Llz3p8UBs2EvBITQX4+FeYRWKwW1hW+QGCH/xLQ7gt0Xf7DnbF+pEx6DWIHu8xVFIV3Vh3lf2sSyrJXwztCZA84tKQuL0VyHjgHa4PEA2+sOOxy598pMohZ41wdxhUJgxMZZX6b9uGBABxcOpOtfj5M7XINmkqa3VcFKQyaCfmlJkL0Fbe+W5CwgFxLIobMC/FJvpJ7sgvJ0ur4V+JvjkSlf05m85xTshK4mhTocgkkbQFDQZ1ch6TucK5iWuoePCA5Jz5cexxQS8VP7h3N5D7R3HVBBwACbCajIqN3YbA7STXVdY8OYWr/tigHF/NOzi5aaPyYPuihWtmjFAbNhNxiE6H+3oWByWLivV3vEeXXHWPGRB4t2c9duXn4pI9hx9kdbEjZgNli5bqPN/PtllNkOMVKlzgLg44Xq1FFibLQXWOhb0wo4NrUyC7gx3SNAJDlrs8Bk5Nj+PkpPXl/+gACfH0I8PXh6CuX8vkMVeu2l6Y+k1tCUnaxyxpJOSVcPyiW5Q+Npq1PIatWPcpWfz33DniIYN+KTb9VRQqDZkJ6QSmRIX5ej69LXkd2aTZPDb+PRwbquEG7hu8tY0nLGUeYPoxfj/3Ksv1pjvkpTslIJc4x6rFDQRcAx/+qk+uQnDvhga4FzCKC1c+FyVJeGPSIDgEgIb3Qkf0qqR6zftoNwIzh7bnZzVfg66NBbystYTRb2ZiQyYjX/2L0m2scc0pNFjIKDMS09AdFoXjRTN4I8qFbcBzXda96J7PKkMKgGWAwWziZUURksHdhsPLUSsL0YVwYO4oblaVYEbxvvgKN0HJFxytYm7SWsyWnHfO3JWY7HruYiXz81PIUCavr5Fok50ZeiYmsIqPjuU4rGBofDkByTtndaE6xEa1GEGWLPhv/7jru+XbH+d1sE8Eeyff4xG4ej9uzwA1mK9sTyyK3/jiQxouLDzjel3YtfGHxQ3yUsZV0Hy3/GvUyPprayxuWwqAZkJRdQpHRwsD2nkNCFUVhR9oOhkYNxcdQSNjRn1lsHUEGLbEqML3bzeh99Kw48wn2DgipuWVVLl3MRACdJ0D2cUjdW1eXJKkhCenqF1OYTTt4/rIeZBerwmH8u+tYuDsFgJScEqJC9C4RMGuOZJzn3TYNSs0WrujXxuVv6Yw9m9hosZJRWPZ/dde3O/hyYyLj3llHMMWM2fkguw/8yLctQrmy05X0i+xXq/uUwqAZYFfvWwR4rm+eVJBEekk6A1oPgJ3foDEXEzzmQR68uBMAIb5h3N/vfo4WbCMg7n8EtP+AzZkL0bXciL7tt+zL3OO6YK+r1XDUPT/W6XVJqo/dFh1nD090a3P60DzVpJGcU0JMS39HaXNnVuxP5ebPt5LnXM8o6zgUnK27jTdiio0Wh5PYE75a9ZjRbCUx09VXILAyQbONeX7P8mXJHm5r04bWQW14eODDtb5PKQyaAWXFrTy/3VtS1czIYdHD1HIS7YYzYewEQm3Cw2ixMr37dC6IvBaEGbSl5PjPRx+1GF3IAd7e9yibzmwqWzAgDLpeCnvnq4XtJA2GAlt442MTutImVM/47q3xFEWalFNM25b+Hj8z76w6yvpjmVz1wUYyc/Pg9/vUxMS3u8KSh+V77kaxwYy/zrs5x24myio0sCcpl46ROnSBBxkY9i3TYp/B2u577miv4/PQYCZ1vIwfJ/9IS72XxM9zQBaqawbYoxR8vQiDzWc2Ex0YTXt8IeMQjH9JnW8rXWE0WxFCMCH6dpb+PRBQ0PiloSg+YPGnc98feHTtoyy4YgFRgVHqov1uhEOLVN9B14l1fo2SqlFsEwb92rVg09NjgbLy5nbSC0o5m2+gR3RIOc3gknfXER7oBxRSkJHMqXceo5XmGAybCVYT/PMJlObD1Z+d12QFo9nKw/N3M31oO0Z0bDiFEhVFodhUsWawMW01gZ1fYW6CgiZGR6YuH324laNAigIx+jjGth3Ctd2uo29E3zrba6WagRDiCyFEuhBiv9NYmBBilRDimO13S9u4EELMFUIkCCH2CiEGOJ0zwzb/mBBihtP4QCHEPts5c4WQ6S61jaeyt3YKjYVsSNnABTEXIBLXqYMdxgCgs9WmsIfGlVW7FFgN0SjGCBRLENe3exaLYuGFTS+UhSB2HKuWrZC1ihoURQYzQoDe6bPgHEUEcDxdTXBqFxZQTjM4craAzSeyuFizk+V+T9FdnOZe40P81+dWmPQfuPhZ2P8L7Piqri/Fha82nWTp3lRu/HSrSyhnfWMwW1EU18Jyziw4toCXtj5DmFkwrqiYSYYUpufn8uQZLf0TprD55t38csMqXhn9ap0KAqiamegrwP3W7ilgtaIonYHVtucAlwKdbT93AR+CKjyA2cBQYAgw2y5AbHPudDpP3kbWMp7K3tpZeHwhpZZSpnaaqpamDgiH1r2BslopKw+oIaUlbmWObxmuhsn5i9Y8PPBhNp7ZyH+2/0cVCD6+0OsaNRu5KLOuLk1STYqMFgJ0WpdM9F5tQ13mJNmiV0L9dbjfm4VQyFu6j/jC9y3SlZZMMb7CcuvQskJ3ox6FDhep5qLtX9TtxTjx72VlJTOu/3hznb3O0r2pfLM5scrz7cmZAR58Lz8e/pHnNz3PMBHIH2kHuS3Th8jUi3jw8p+JnLKccZPuQmi9axS1TaXCQFGUdUC22/AVwNe2x18DU53Gv1FUtgAthBDRwCXAKkVRshVFyQFWARNtx0IURdmiqLeU3zitJakl7CWLPQqDhIX0Cu9Fr/CeqjCIvxA06rzELPUO8eftyUD5Usa9bV8iJSYLN3S9gZu638S3B7/lwz22muqD7wCL4bzfJUq8U2Qwu9QdArh6QFuX58k2J3OLAF9HJc0QvQ89xUlW+j3FVM0G/oq4hZej/8ekiy50nLcvOU/97NzwPXQeD0segWOr6viKysygdnaeznVETdWUrEIDi50qt9qZ+cNOnl94oMrrFNuyigN8Xf/mG1I28O+t/+YiI7x34hCHusxiqvEl3rNchT5uCBN6RXPL8LhzuobqUlMHcmtFUewNPNOA1rbHbYEkp3nJtrGKxpM9jHtECHGXEGK7EGJ7RoYMc6sqz/6uWvjczUQZxRkcyj7E2PZjIfMoFJ1jZJUAACAASURBVKQ6TEQA941Ro4ku79dGnV9gcElYsocnlposCCF4YvATXN7xcj7e+zEHMg9AZDeIGw27vlV7JtuwWhWynWLdJeePIqOlnDBwv/t/b00CoGoGQ+LDeHZydzZfr2FJ0KtYEVxpfIn17e7hy7uG0a9rMheOWIt/u4/5dt/v6gK+gXDt19C6F/x2J+Sl1Ok1nc0vLTc27p2/z2nNWT/t5oEfd7nkXjhT6h5O7QW7ZuDcZzyzJJN//f04nU1m3sw343vrMgZMe4E5N/Rn0f0jz2nf58I5RxPZ7ujPS666oiifKIoySFGUQREREefjJRs9iqKQa6tHH93CtXz1hhS1ZMTotqNVrQBchIH9y94eelhqsjjGAIL1OrQa4TAfCSF4esjThPqG8t+d/1Un9bkechIhpazf69QPNjLg5VUUVVCyV1I3FBvMFTozoUxutwhQzUR39ITAhbdDWDxTjS+yXxvGceNCLvnlEmatncXRwg1ofLNYkf4Oa07bMmd9A9R2qGYjzL8FSvPq7JrWHEmv9TWzCtWblR2ncoh7ain//dO1+Uy351Zw73eVJ+E5zES2v7lVsfL00lspNuTzH3ML9Hf8Ce2HA3BFv7b0iWlRm5dRLWoqDM7aTDzYftvfjRTAuah2jG2sovEYD+OSWsLemOSqAW0dDmE761PWExkQSZeWXVRh0DIeWpaly/u6OZBLTBZaBJTVN9LrNPjrtC5F64J8g7i99+1sSd3CtrRt0H0KaH1h38+8ueIwO0/nsDdZ/WJI8nLXJak7Cj2Yibyh12nBaoFf72Sbrw+PdepDSee5BHV+nV2FP9ItvBsfjfuIdTesw3L6cVr6dODRvx/l7yTbXXl4R7jqY0jdDf/tA4seUH1I2Sdr9ZrWHE6nQ0Qg65+4yGX8XOopBdocvva8C/fmPwDLbeVZ0gtKKSj1HE6bXaTW8Aq2FYn8ZsVMthSd4gltFB1v+8OlJHx9U1NhsAiwRwTNABY6jd9iiyoaBuTZzEkrgQlCiJY2x/EEYKXtWL4QYpgtiugWp7UktUChrSyue7idyWpi85nNjG47GmG1wMn1LloBqF3PfDTCIQxKTRb0Oi33XNgRUOuz+2gFX2w8SaKTP+H6rtcT6R/J3J1zUfSh0GUiyr75fLb2MFd9UJaPkJQtm62fb4qMZo+NVey8dlVvl+d5/3zMc4YT/F94IDuyD2Mq6EVp2hReH/o1H437iJFtR6LT6PD3CWB4wJN0btmZh9Y8xOLji9UFuk+haPpiFpf2xrz3V/hpupqTsPJfYD23qB+j2cqn605wMDWfXm1CiQ0LYETHcMfxgnPQPN0jrAB2nHJ3naolI4a8uprJcz0XZly0+wy+Php6tQ0hee+PvJ+2jotECNdMWwZ+tVNgrraoSmjpj8BmoKsQIlkIcTvwOjBeCHEMGGd7DrAMOAEkAJ8C9wEoipINvAxss/28ZBvDNucz2znHgeW1c2kSgAKDesfingq/O303haZCRseMhjM7wVhQThiAGl5qd9CVmKzodVqenNiVFbNG0yEiyGGCenj+bsc5eh89d/e9m90Zu1mfsh4GzEAUZ3GZxjXKw70yo6RusVgVTmYUER7kvUZVK9ux0Z1bYTUbeWL/hywJCuKWHrew/OrlTIt/jH6hlzG52wCX83RaDUIJ4PMJnzOo9SCe2fAMn+37DEVR2C+68kDpvfQsfJ+Hg98ir/s02Pw/WPaoiy+pujz68x5eXXaIs/kGh/nysxmDePpStQaQ3dRTE9zDU7UaweI9qpu0e3QIz13WA1BLRgCczi5GURRKTRZmL9xPen4ppSYLi/ac4bpBMeiLUnhpy0tohYZnrvgeofP+HtQXleqLiqJ4K4s31sNcBZjpZZ0vgHKxZoqibAd6VbYPSc2wawbBete3evOZzfgIHzXreNP7gPDYTNtHIzhjq0NksGkGQgi6RYW4zHOvf39lpyv5cv+XzNk5h5GT5qFE9uKRs7+w1DAMA+o/7ktLDvJ/o+Jr61IllfDkr3spMlpo46H16dxp/WkV6MvwjuGsnHUBXaOCWbpuNpt08GzcVK4f/DgAL1ze0+Pavj4aDGYrQb5BfDDuA57d+Cxzds7hZN5JxoTfC4ABXxZktOGPvFgOjG4FG+dAeCcY7vEro1Kco33siXMBvj50s1VazSo0EN8qsEZrOwc4RAb7kV5g4MCZPLpHh7D8odEYzVZeXnKw3DnztiXx9eZTfL35FB/dNACrAiPjQ/hhwTQ2+/nwXO97iQqNq9Ge6hpZjqKJY88VcNcMEnITaB/SnkBdoOoviO6rlpFwo8BgZum+VDIKDJSYLPjrXD8y9n6sh1LzXcZ1Wh0PDXiIozlH+d/eD8gc8SwxIpOHfH4DQPjko/FLo6SChh6S2uWXHWrgnp+HmPfL+7ZhRKdWCCHoGhVMqamEOSd+p7sFrh01u9K1fbUah2nFV+vLG6Pf4L5+97Ho+CLm7H8Mjd8ZtIHH8Andjsn/H84Ov1f1J638Fxz4vUbXo9OWRUGl5ZVFFIXYbnwKSs28/ccRtpzIqvbaqU7rXdZHjabblpjj6CHunM1vFzgDX/mT/zi1gb3nOzVoIjrh37wr8hkT2pVr+99b7b2cL2Q5iiaOQxi4aQYn807SqUUnMBRC0j8w4v5K17H7DJyJDPbjtBdzzyVxl7A+ZT2f7fuM7a2G0DK4D61919Nef4BsX9W8NHXRLzwwYCaT4yeXC3GU1A0xLf0rnfP++n+RKqy83OGqKrVU1Gk1mJzi/YUQ3Nv3XuJD4nlq/TMEdnCNzR/36890a9GFJ2L7MvjX29Ugg26TqnUd7cMD6RgRSHyrIKYNKYtPsd/4HD1bwHt/JfDN5lPsmT2hyus6F+4DmNwnii82qk7v1iFlWtWUvm1IySnmw5sGMvTfHkq2CzMvdV7C89nrCfIL5IVLPm7Qn3EpDJo4dmEQ7KQZmKwmkguSGd9+PJzapNaU6TCmwnVMFis5xaZywsD5DumFRQfYm5zLT3cPV23IQvDKyFfo06oPr//zFuZWpfhYQxhams/QEg3LSwZR0rGIp9c/zc+H5vGfi94hMiCy1q5d4srguJZsS8zh8r5tvM7JLc3lvV1zmZ+0iuuLzQwd8WSV1tb5CI9lICbGT2RHgpavdqzj8xsns/GIiU83HEYbmEBx8H7u0OXybptuXPzzDLjhR+g8rsLXsVoVvtt6iou6RlJYaibUX8dTl7r2CQjS+yC0hby2cifgR4mxegaQNYddQ1Vbh+iZ1DuKZfvSiHISBu9N6+94HNcqgFP5p7h6uBm/wGQScg9wLOcI/0EhUKvnvXHvE+4fTkNGCoMmjt1n4KwZJBUkYVbMxIfGw7G14KOH2GEVrvPmCjXd37mpDeASrvrVpkQAtifmMNwW1SGE4Ppu1/PkV/6gMYLVn49mRlCw6EluK1mKdT/8HhTIG9Zd3Pzb5Xw8ZR5xDdSm2pjILjKyZO8ZJvWOJtRfh49GcCStgGlD2nm9Oz2YdZC7V91NgSGPm/LyeWTUy2q+QBXQaTWOTHd3AmiPKXcYI2OGsvtYAlZDPlZDGz4b9zSPrLuXJ3OP8XlkJ/rMuxFu/Ak6XuRxHYBJc9dzOK2AyX2yySk2lmvlWmAsYO6eNwnqUmZ6UkxhbE0NY2j00EqvQ1EU7vhmu8tYqL+OPUlqOHTPNq6+suSCZH499iu69ksIKk5jZToE+gTQy2DgpoI8enaYwPDx/yFEX3/5A1VF+gyaOIUGMxoB/k539CdzVZW3Q2gH1V/QbhjoyjsVAR4c2xmAPw+pd0suNexRSyG74zm+WwtWf7Y/Ow5ih3Byyi/MND7I/zQ3c8WE9/jCvwelxnxuWXwd+zP3ezhfUh3+s/Iwzy88wKBX/uTxn/eQnFNCfqnZUULEnbSiNO5ffT/+Wj/mZ5XypH8ndP1uqvLrOUedgetnoNhoxl+nRasRjpsEgE3HCnlv7HuE+7fiziAL6yLj4PtrYf9vXl/ncFoBoNYIMpitRAaXfW4PZx/mqkVXsSxxEcaskZSmXYYhYxxaoWH2ptlYrJVnDf9zsnz4aKCvD4+M70LrED8utPWEzizJ5Ml1TzJ5wWS+3P8lHVt2ZPbw2SwY9TYbzxbw2dksHrnsSy6Z8mmjEAQghUGTp6DUTJCfj8vd4Ml8VRjE6UIh/YDaptIL/WPdPshu3/O9Y0IdeQd23AWG3Qb70NjOjtDFAL0fS63DeKf4Ur4vGkjMZd/wjW9nAgwF/N/yGSw4tqBa1ylxxewUJ//77jOk2Uo2ePIXFBoLuW/1fZSYS3jfvztd8tNh0puOGlVVQXUgq8LgeEYh3Z9fwW87VYd1qcnq6PM7OC6MdY+rd/7fbz1FK/9WfDXxK+JC43nA38BPsd3gt7uq3EPb3tf7VP4p7vzjTgC+vfRb7u79CKacURgzxxFQNIWUwhQ2ntlY6XrpBWqS2PKHRjvGNBrB1QNj2PrMOHRaDTvO7uCqhVex+vRqZvSYwcqrV/LRuI+4JrQ7nX69B63VArctg44XV+kaGgpSGDRxCg1mR/ajnZN5J2kd0JrANNsdeLsRXs93z1q+emBMuTnufRLsd2927G0xA53K+DqXRHh+4QFu+Hw77a/5hm+VaHoX5fP8puf5+ejPFVyZyo5TOQ6/iKQM51ak3aNDyLcJaHezCsB7u97jRO4J3h7wGJ13/gD9p0PbgdV6vVZBvpzKKuZwWj6bEjIpNVn5aZtajsxksbp8jtrZuqztPJ3LnqRcogKj+PKSLxnddjSvaPL4d5t2mH+6Gc7scnkNu+Yxa1xnx1hksJ6c0hxmrlbDUz+f8Dl9IvowrnskUcF+zAjdzZO564jwCeSHQ99Xeh32z5I90949JHvpiaXc8ccdhPqFMv+y+Twy6BFaB7aGtP3w9RTQ+qmCIKp3ubUbOlIYNHEKbZqBMyfzTqr+gtOb1faUbQd4Ods1fA/gztEdys1xrobqr9NyPKOsYmSJ0UKv2SsB18qNzjWOwBaaqg8lYsZSPgkZxMjiEv695RW2p7nab50pMVq4+sNN3Pm19znNFedCam1b6Cnwkm9SZCpiQcICJneYzIj9S9Wonoufq/br9WobSlaRkYn/Xc9ztqqeW09ms2jPGYxuwgDgzav7AJCap2ahB+gCmHPRHGb0mMGPOhMzI1uS/8O1kH3CcY5dwDnf3JRyhunLppNamMqci+bQLqQdFGfTJ20BW1q/wYuGNxlr3cr1GSlsPLOJI0cXVZj57PCx+fnw3rT+LHtQ1RAMFgMf7v6Qp9Y/Rd+Ivnw36Ts6tLD9L+Sehm8uVwXBrUvUMhyNECkMmjBj317LigNpjlLUoNpyT+SdsAmDLdCmP+i8hxq63/W7Cwco+4cG6Nw6yCXzM7PQ4HjsWtdIy8nXPIQS6vzRXv0Jbxr9iTErPLL2YVIKPZerspcH3nwii4//Pu71GpoLiqLw4drjPDJ/Nym5ZXHyhQazI27eXTP4I/EPSswlXNuyD+z/FYbdC8FR1X5tb/21H/xxF7/tTMHH7XMzxmZ7t5tlALQaLY8NfowXR7zIP74+3NTSj/0/TIXCdLIKDdz25T+A+plc+9iFXD0qn39tvZsiUxGfj3mXAalH4Icb4K0usGQWlOSwov3jDLd8xvUDHyLMYuHpvx/H8HosfHsl/P0m/PMpHFjg6LlhL2ER6OvDlL5tiA0L4GDWQa5ceCUf7PmAS+Mv5ePxHxPqZ/O9WK2wcCaYDTBjcaMVBCCjiZo0xzNUIWBwcuxllGRQZCoiPihGLUMx9O4K13C/o/MUiTJ9aHu+23IagOhQvUvfg5ziMsHQp62r/8F5LZesWL9gQia/y3vzrufGWA0PrH6A7yZ9R4DONbLFuUDe238c5e4LG+8/Ym2wKymXN1aUNXkZ3iEcrUaQVWTkt53JxIUHlNPIfk/4nbiQ9vTd/AkERsLIWTV67ZJKSjq7l4YID/KjbQt/ft2RXK5u/1WdryI2OJbH18ximk8+U3+6lOPGf7HztB8IE2tTf+abpBWkFZ+lsyaA/6Vm0OaLK0CxQkhbGHYP9L4WovpwYNVRio8mEDrqUV6O6srMTc/wWofezM5MRqx51elVBXQaS7RyCZF+kWhyE6Eok1M+gnv+fhg/rZ5Pxn/C8DbDy06xmGDjf+HkOpgyB1p1qtHfrqEghUEzYEC7si/hk3mq8zjeZAGLEdoN93Ya4KoZOK/jTPfosnC7EL2Oo2cLKTaaCfD1Yf2xsi5n7iW0QbX//vfPYxS7f5l0Gkfc6Cd5a8vb3It6R/fu2PfQiLL9OJtCPGkszY10t7r+7cICKDFZ2JBQ9h44C+CEnAR2pu/k0XaTEXs+hClzQe8aOllVpvSJ5pUlB+kX24KtHiJy3P06Wo1gcp9or13DBkcNZsnVK/nk72f4NuUvdPrn6R2vJV2n8E++wtCSUu4uKmKyIRP/bpdDWLzaUKfNAJfey2GBvlgV+GJjIrePmsIdBSf4bN9ntB59H/f2uFVNusw7DUdXws5vmFbwJ9MEMBeSfLTcHdUaNIJP8yzEbfseOqSo/zdHV8CxP8FUBF0nw4AZHq+jMSGFQRNl4W7VtDK+R2veurasd6pdGHTItdV1ia049tpZM3Bexxv2sr5fbUrkvjGdeGdVWR14dy0DYNa4LlisCu+vSUBRFFfN48InGBHYisfWz+ZN1vH+5ld5YESZPdtZMygxWbBaFZd2js2NxCzXTPAxXSP4+2hZE6gQN3/BL8d+QafRcUXibghtB/1urPFrtwjw5cgrl6IoCvFPL6NVkB+/3DOcS+es96o1hPrrKDVZKTSYMZqt5bSWIN8gHhk/l6sO/c7za97EKIoYWqxwc3gnBrcbAq06q8mSga08rg9wcbdIXlx8kJeXHOT2UfE82P9B0ovT+WD3B+SU5jBrwCwC2g5UHeYXPM6Hn32Ib/ZRxo7pzK0n52G0GPk4eiJxualwcKHaqAlULarPddB5AnSZ6CKAGitSGDRR7HXYx3WPdLETn8w7SaAukIiUPdCqS4X/SOB6x+3uiHbmt/tGYLUq/LIjmXnbkhwZzx0jAskqNPL7TO8dnEL0OqyK2oVryZ4z/HMym7sv7EjXqGAY9H/c1LIDx/64m0+OzSekKJtbRs1G+LdwfMlc1DWCNUcyKDCYPUbLNBec6/MAdI0K5k2nWjlznDJmS82lLDq+iHFRw2i58XsY+zxoz/1vJ4Tg29uH0DEiiDYt/Fn8wEjGvbPO41y7D+m+73ey7mgGCa9eio+HG4a47lPJW92KPcl5fHf7UAZ3rvgz60z78EDatvCnQ0SgY38vjniREN8Qvjv0HYuOL+LqzldzV5+7CPULZb1mCNktIvk+6RMUrS/fTf5ezccBtVFP5lHQaNX/Hc356098PpDCoIkSFaInLb+Usd1bu4yfyDtBfEgc4sAWtVBYJfg6/XNW1BRlQLuWgBrqN29bkqNshVajYUD7lsSGec9kta+7LzmPp37bB8Dqw+mOejKi4xievWYRBYun8daZP9n7xUJeMujpY4ZtfgWYzwbwe1Abtu0LZtyQ8pVXmwslRtc78KhQPdOHtuOVpYcAaOEkKFcmrqTAWMC1Fj0goPd1tbaP0Z3LuhBW9JmxC+51Nu3l2y2n6BARxIVd1PNLjBZHu8gSk4WJPaMYVQ1BYMeei2DHR+PDk0OeZFL8JL4//D3fHvyWn4/+TFvfgRwsgIDwHYSLED4Z/0mZIADw8YWopltgWQqDJkZSdjFL96XSJSqY1iF+jiQvOyfzTjKkRVcoyam0BAW4+gwqa5cIOJKLkrKLySkyYjRbykUkuWOxhfpN+3SLYyyvxERBqckRRugb0ZV3Zmzjqw2zmZO4iGPBevqlBZDaohX7w/IpJBPtwfu4Nu8iHr/4bXy1nqNbmjIGc5kweHJiNwJ8fbhjdAduGR7HpuOZ9LcJbFAdx+2D2zPoyGqIHw0tYj0tec5UJAxa+Lu+Ry8uVktC73xuPGdyS7jsvQ18cvNALuwaQV6JqcZan0YIR4lrZ3pH9Ob1iNe5redtzDsyj/kHV6ALK6Fnq768NeYNogKrH1XVmJGhpU2I9ccyGP3mGl5ffpjj6YUucf2gxpSfLT5LB3t0UbvKhYGznb8qFRft5ZHn/pXAiNf/wmC24udB9Xfm2kGuX0T9bY7qnCLXTGah1XLbha/wyYTPSBU6FrTOYnPLXIbEjqFn8bVMKlSYd2Ytt/4+lbSiNMd5649lcP3Hm6vcxLyx4txT4rI+0Y7Hvj4axnQtKwCYVZLFjrM7mBTWC5GTCP2m19megv18iAj2Y8bw9uWOOYcaO3MoNZ/529WEtbu+3UHXZ1dwNt/gdX5laIXwmFqwZO8ZHvhxF20COvD8sOcpOvYsHQv/x3eTv252ggCkZtCk+PtImbMwNa+EblGubfUS8xMBiM/PUB1gYeUTyNzx5PStCOcEtBKTBaPZip+u4jX0Oi0TerTmj4NnaRXkyx2jOjDzh51eHY9DoocwRPs2y44d5tr+HXjz4guYmbqT/akDeNfvFf6Vf4rLfpvE1M5XMaPHDG7+fC+glkno2cZzbZ6mgHMRwYr+5hvPbERB4cLMZPALge6X19mehBBsfXqsR8e+czloZ6Z/ttXj+PgerT2OV74HsHjQDF5ecpCz+QZGdQpn56lcAC7tHV1uXnNBagZNiJzisjtpqwIBbir6iVw1mzP+7BFVK6jCnX51Qzb93ExCRovVxe/gjSm2ssrDO7bC31edX9GdfIlRS8+Ijrx5peojCA3QkVLix7gbl/JLSQCXFRTw29FfmbRgEkFdnyOw0795f98rjr9BU8NgtpBl6871znV9XQq4ubMueR3h+jC6H/4Tel1d5cqkNcVbhFdEcJkJ8/FLutI3JpTYMO8JkIPiyjdfqtLrC+GxeKK9ZtaTv+7jJ5sm0pwDEKQwaEIcS3etCRTg1nvgZN5JtEJDbPbpKpmIoGqmoYrm5xabKvUZAIzr3popfdvwxCVd0fuUOQ29UWQwu5jBAn21ZBUZOVygI/amRbxgCmR5UjLDMtqgzemPpTierelrmbpwKg+veZi/Tv9Fdmn5ePjGSqmxzA5y1YDy9aPsFJuKWZe8jrEBsWjMJdC/6pVJ65J7LuzIwvtHserhCx1j1w2KIfH1yee8tlYjsHoopGv2MOjuY2tOSDNREyLVLbQwwM9VGCTmJxLrF4aOxCoLAzsdathLFiDIr/K7LX9fraNZSIathMWiPWcY1sFzQ5Bio8XlzvLyvm35dP1JVh9Kp9tFneDOv9AveJRPj6nlkAsUf1KDLmBlx478mPI3f57+E4COoR0ZFDWIwZEDGdxmKGH6mt191jelNudxr7YVJ42tS1lHibmEiemnIaJbtQvS1Tb2/sJam/ag12kJC/Qlu8jo8CXdMDiWlNySipapECHKdy/7+2gGucWmcnMjg6UwkDRyLFaFrEID04e24/utamkI9+ifE7kniLdqQRcAUX2qvPbKWRfQOqTq/yRx4QEuCVCD41pWMNs7P2w9TWGpmX6xLfi/UfEAPPHLHkZ1jqDIaKa9k3mjd0worYJ8Sc6xvW5AGK/pH2anYShv9Utn/75dXJu6iQdOr2R6y678bQklLcjInswTLMpJ4KcjPwEQb7bS22Sht18EvbtOpcvge9Hp6taMUhvYTWq3jYivcN6vR38l0i+MASd3w/iX6j1ZatXDF7pEQYEaAptdZHRoiK9fXfXPqie0mjIz0VO/7mVDQibJOeWFy+jOrejcOuicXqsxI4VBEyGn2IhVKWvODa5VQk1WE6fyTzHG5AMxg6qVYNTVzRFdGWsfv4gvNpzkpSVqqKBzQ5Oq0C+mrOzFoj1nWLTnDLeOiOPOb7az+nA687cn0yrIt1wSXHSoP2l5peQWGzmeUcS8bUlALP5jpvPMrnX4XvQa12jXkb1+HrH5BbTM8actYUyPiOSQTgut8tlnymaDLp9FSi4c+wq/o1/RIbgdXaMGcGfvO9WqmA0QeySRe1tSZ/Zm7GVL6hYeDu2NVuyFPtefr+15JTRAB7h+FqNC9ZzILPLaOa26qKGl6uN5trLadtY+NoYxb63lhsGx5yx0GjtSGDQRMmzVH9u0KHPAOUdrJOWrrS475qTDwCvrfD83Dm3HztM5PDK+S7X9Du4ORx+N4ERmIaudetNmFhrLVcrcl6K2Jpz6/kaHZvLs5O50iAjCz0fDP2cMrCoZwMrMtq4vaKvMwSk1We/BsZ0ICymEzAXs3PMdp0qOsKogiZXHlzJnzNsMb+e9LWN9YdcM9F6iiBRF4a3tbxGmD+P6E3vUxis1qE56Pnj3+n58vuEk/dwbK9UQjc1M5O5Enj60HXGtAmvFL9EUkMKgiWAXBs529O7RZXf0O9N3AtDDUFppPaLaQK/T8r8bvfdJqA4ajWD+9uRy4y29xJ07m6jahwei1Qg6RgR5XKNvbAtyioyczlbPScsv5ZkF9rab/fGnOzdo1/BAyN88G1bEU3/ez69DXqJVr6vP/cJqkTJh4FkzWHxiMbvSdzG70w0EHnoTxr94PrdXLVqH6HlmUvdaW8+edFbklqE9sH3NzJdNFRlN1ESw9w1wjoZwNhNtPrOZSK2/mnAWM/i876+62P0MA9u3xGi28sk6NST05all5QCiQr2HT9oZZPuHb+NWMfXhcV1Y9fAFLJw5knVPlN3pX9AlgteuKutSVYKeLy2XclnOazzQ/V8UaDS8/ffjsHd+zS+uDrD3BXAv9gawP3M/L21+iQGRA7jy5C4IaAXdms/dsBpaCmfcnNBX9m/r5YzmiRQGTYSvNiUCrpqB3YFssprYkrqF4RYtonWvGpcpPp98essgvrt9qEsP5n6xLZg+pB0tAnS0DNC51MABmOtUiC0s0Je3ru1LS9uXY1ub+Wxy72jGdI3gtlFxdG5d3hdyz4UdmDakHT/eOYznL+vBiX9PYuHMkYCAPHLELwAAHGtJREFU8Eu4tdetLAkKZNPyB2H3j3Vw5TXjWHohGuHqMwJIL07nob8eIlwfzrs97kCbsAqG3lNhQ6OmhkajJp1NeNe1YF51zZdNHWkmauSsPnSW3Um5ZNruDAOdIojsRb62pW4j35jPxZn50L32CpLVJS0CfBnVuRWrDpaVlTiYmo9GI9j13HgMZms5k8ikXlFsHtKOge1bclX/ti6+h8cu6colPaMY0clzobP5dw8nwFdLr7ZqhvLwjuEOx7ddqBYbLdzVbyZ/Jq3lObT8vvA+glHOqfRzbXE8vZB2YQEufxNFUXhmwzMUmAr4duLXhP12v6oVDLmjHnd6/tEIgdVTooHEBakZNHJm/bSb9/5K4ExeKZN7R7vc7fjbvhj+OPUHARpfRhTmQVcPrSYbMI9e0pXHL+kKgM725S6E8Ggb99FqeO2q3lwzMKacEzpYr/MqCACGxIc5BIE79kzuYqMZvY+ef49+jUyh8HZcd1j0AJxcX6Nrqy12J+WydF8qnSJdNZ3NZzazNXUrD/Z/kK7HN0DKdpj4Gvg3L1u5RgiXbn8Sz0hh0EhJzikm7qmljkbnAMk2m+htI+MAta6Q2WpmTdIaLsQffUAExDeuEs8heh13jlZrKF03uG4qa1aGPZPb3kynV6tezOg5g18pYFNEHMy/BXJO1cveAP7vq20AdHGKkVcUhTm75tAmsA3XRY+G1S+pjWB6X1s/m6xHNKKsXzaoHeCkv6A80kzUSNl6onwphctsRbaev6wHs6f0VOelbiW7NJtxZzNh4L2NsiGHr4+GfS9MKFeF9Xxhz+ROzSt1dGOb2W8ma06v4QX/IhbkZxA470b4vxXgV72cjNrA3sfAuQf0n6f/5GDWQV4e+TK+q55TWzVOfqfek8zqA4PZ6qjb1bV1MEsfHOWxiU5zR/5FGilpbv1uAe4YrWafOpuKPtv3GZEaPy4sNcCg28/b/mqbYL3OUbLgfOPno6VDRCCfrDvBkr2p6pjWj5dHvkxaSSbv9psE6Yfg2yvVPhHngUKDmfu+38GxswWUmCw8Or6Lo8ia2WrmvV3v0SG0A1PMvmq7xgseh/COlazaNLG3YgW484IOUhB4Qf5VGimJmUUE+/nw0U0DuKJfG168vGe56IjtadvZfnY7t2WcxW/ADAiVqnFNef6yHgAcSSsrBtgvsh839biJn9I2snXi83BmN3w9BQozvC1Ta2w4lsGyfWlM+d8GANo7RREtPr6Yk3kneaDXnWiXP6HWIBrxYJ3vqTHgLSlPco7CQAiRKITYJ4TYLYTYbhsLE0KsEkIcs/1uaRsXQoi5QogEIcReIcQAp3Vm2OYfE0LMOLdLah7kFJuIDQtgYq9o5tzQnxkj4srN+XjPx4QpGq42+6o9biU1xh5Z5O9W7+mB/g8QFxLHM6cWk3nNp5CZAF9NgryUWt/DFxtOEvfUUpbuTeWe79QkwlKTlVB/HWO7qc1rjBYjH+75kJ7hPRmbsAnykuCy/6otGyXEhde84GJTpzbE5EWKovRTFGWQ7flTwGpFUToDq23PAS4FOtt+7gI+BFV4ALOBocAQYLZdgEi8U2w0V9iGck/GHrakbeG27Cz8J7zS7CJIahtfrQYhyvdY8Pfx580L3iTfmM+tRz7nxFUfQH4qfDkRsk/W6h7stZ5m/rDTZfySnq0d7SV/PPwjqUWpPBQ3BbH1Ixh4K7QfXqv7aMy4N3ySlFEXOtMVwNe2x18DU53Gv1FUtgAthPj/9u47uqoqe+D4d7/0QgKBJEAIBEMTRQFjoYgKElFUil1E9IddB0dnxq44jhXLODoyM4CKzij2gjoUg6gMIL1LC00ghIRAentJzu+PexMSkkDKS957ZH/WyuLm3Ptuzt0ri5177j37SAfgEuB7Y8xhY8wR4HtgRBP066SSV1xabfGacmWmjDdXvkbrsjKubdMHzry+mXt38hERAn19anxF8dS2pzItcRo5xTncuHYKCy59Copy4J0RkLbFJT9/28Gcam1PXd6bWwfF8ZJdYC3PmceMDTMY2GEAA5ZMh+AIuPhpl/z8k4U+L6hdYyNjgPkiskpE7rDboo0xB+ztVKB8rboYoHLJwH12W23t1YjIHSKyUkRWpqc3/bisO+QWlTDs1R9ZtjPjuMcVFJdUmWBWzhjD66v+yrK01fzuSDbBI//aIt8gaQoBfo5aV1/rF9WPjy//mFPCT+H369/k9QE3UYqxhoxSNzT6Z5fPnj21gzV7/O0JCfzf4K5MvuLos6L3N71PZlEmv/OLgZQ1MOJFvSOsZNKw7u7ugkdrbDIYbIzpjzUEdK+IVHmJ3VhlAl029c8YM80Yk2CMSYiMjDzxB7zQmt+OsCM9j5fnba31mKKSUrYdzK02fg3WBLN3N83kuuwcrul7F0T1asrutiiBvj7HXYqzfUh7Zo6YydU9rubtXV9zZ68EUv2D4L0rIXVjrZ87EWelUs5z7j+f3S+OZNipVdcDTslNYeammQzvOJjTl06D+GHWkpaKF8f2YXC3djw4vIe7u+LRGpUMjDH77X/TgC+xxvwP2sM/2P+W1x3eD1SeNdTJbqutvUVasNkK16HcoqMLtRzjqzVWeI5d3N1Z6uRvK16hW7GTR9skIBc+2rSdbWGCA3zIK6o9GQD4+/gzecBknhn4DOuzkhkb2Yq5wUHw/pVwcFODfm758p9PjKy5kufOzJ3cPOdmHOJgUno6lJXAyFf1jtB2/Tmd+c9tTV+p19s1OBmISIiItCrfBhKBjcBsoPyNoAnA1/b2bOBm+62i84AsezhpHpAoIm3sB8eJdluL9KG9StnujHxue29ljcdsTc0F4NZj3iD6ZMtH7M1P5cFcJz6j3rIqdCmXScsu4rsNByiuQ2mDMd3H8PmVn9O1dTx/CvPhqfAg8t6/0pqPUE+1lacuM2V8sf0Lxs8ZT0lZCTO730zctu/hgoch4vgrnil1rMb8bxEN/E9E1gHLge+MMXOBF4HhIrIduNj+HuC/wE4gGZgO3ANgjDkM/AVYYX89Y7e1GB+v+I1fdmawJTW7yupOW1KrPjQ0xrBwaxpLd2ZwekxYlfo7hwsPM3X13zi3oJDBQ5+HVlWHEVTj5RZZJQ2S03LrdHxsq1hmXjqT2/vczleBPoxuG8RPs0bV+6Fy+WL3lZPBjswd3Dr3ViYvmUx863j+ff7L9Fz4CnToq3MKVIM0eH6/MWYncGYN7RnAsBraDXBvLed6B3inoX3xZou2p/Pw59YDxvLFWkSgfFGmopJSAuy1YOdtSq14v3zi4KN/+ZWWlfLkj38gv7SQR0N6Imd4R2VSb9OrfSu2pObwzfoUosICqqwdURs/hx+T+k9iSKch/HnRY9zns5cRX47l4ZHv0q5T3YYuyhe7D/Rz4Cx1MmPDDKZtmEawbzDPDHyG0SFdkY/GWSUnxvwTfLTKjKo/HUdws437syu2j+Q7mTCgC3PuP79iDsFbPyQD1kPE8kQAMGFAXMX2y8ue4+eDK3kku5D4y/+uY8VN5P3/OweAf/y4g4Rnk8gpdNb5s32j+vLJ6K+5t/v1LAhwMPL7iTy14PesTF1Jem4BR/KKa/1s+R1JRvFOrvvuOqaum0pil0RmX/EZY37biEwfaj0nuOVbiHLdCmGqZdE/Idys5JhFv0f1i6FX+zDWT07kwld+5N3Fu3E4pMpCLi+M7UPntsEAfJM8mw+2fcr4rByuG/kutIlrzu63KFFhgcRGBLH3sFUddvzby/nq3kEAPPrFBmYt/42Zt57NhT2jmLFoJ/nFpdx1QTz+vtbfXH4+ftw18HESOwzgnXn3MndvEl/uW4AxPhhnawZ26U5MaAwxoTGEOCJZvSeP2DZBvLlwO/7tUvjrrz8RERjB34f+nQvK/OC9MZC+Gc68ES55zppXoFQDaTJws5SsAtqF+nP1WbFsSsmqWNnL18fBuHO78NLcLbyetJ3Xk7YD8OFt51bU5d96eCvPLHmKswsKebDfJIj3vIXaTzbliQCsdQTKzVpuPfi/5d0VPDHyVJ79znpQ3KlNEGP7d6pyjlO6DuXZsV/y2MyRzA/w5bnSgeT4FpPvzGfergXklhw9L4cgyP748C4jeCL6AsJ/eBV2/QStOsKNn0KPxCa6WtWSaDJws31HCohpHcQjl1afDxAdVn1MOqaNtVxhdnE2D8y/kzBnEVMizsF38ANN3ldV3e5DecQds9RkeSIAOJhdVPMHo3oRPOEbhkxN5Fx+5EHn3SxOscqOI8U4/I7Qu2MwUphF34BUbo8vpPOWxbBwGoS2h+F/gbMngr/W2lGuocnAzVIyC+hRw1q8YJVtPlaXtiHkFOdw/9yJHCg8xDulbWg3ero+J2gmp0SGsDM9Dz8fwVlqSE7LpWPr2tcTfmnuFn7alsadQ+K5yC4mB7BkxyFCAzryp+LHedv/FWb5P0dyWUf2mkhio9sSFuhLZN52JNOub5TmgOjT4Yo3rPIivid+eK1UfWgycCNjDPszC7ioZ1SN+6sXoivjs22f8dbK18gszubZXEO/mz8D/+Cm76wC4PsHLuCHLWn069yahGeTmDJvS0WRuFsGxjFzyW4ANjydyJApCzmS7+SXnYf5ZedhxvaL4cnLe3Mwp5Abpy+zz9iZnxPnMDTnG8L3LaVtTgptJAUKSiH6NDhrAsQkQMd+EBBac6eUcgFNBm6UtDmNQmdZrX9ZWuUmSvEJ2kPPuMP4hCzjz0v30rewiDeIoM9Nn0JYx+btdAvn4xCG9z46h2PbwVxumP4LADed15lzu0Zwfo9IQgN8efGqM7jz36sqjv1izX6+WHN0cn37sEAu7BnJ2HPiCfT7Q/NdhFI10GTgJqVlhtvft2YYx0dV/4svz5nHzK1TCO31X0TK2Av0OOLktaxcLu53J3LBw1qj3s16Rrdia6Vqoh3Cg6osSn/Jae1Z9NBFdGwdREZuEY99uZGkzQcr9n87aXCd5ioo1Rw0GbjJ3EpL8Q223w4ql+/M5+7v72Zd+loSs0u5tDCDs4tKaH3mjXDtQxDe6djTKTeYMSGB+2atYZ39VlFIDSXFYyOsIbyosED+Nf4sjuQXk1XgZN3eTE0EyqNoMnCTzAJrktHndw+osrZvQUkB9ybdzfr0Nbx8MJ1TSuMI6T+R1gPHaYkJDxMbEcwHt53LLe8sp3+XE5eK9nEI7UKtmcvxkTr+rzyLJgMXcJaWcclff2bSsO6M7le3dYZzC61ZpT3bh1W0FZYU8rv5d7A6bS0vpGeQOOAhGPyAvinkwUIDfPns7oHu7oZSjabJoJFSMgsY+OIPAEyevem4yeC291bQs30r+sW24YU5W3AIFQvUOMucPDh3IssPrePZzHwuG/Uu9LikWa5BKaU0GTTSxv1ZFdtZBU4ufu0nktNyWf3kcCJCjj7gLSopJWlzGkmb0yra2oYGICIYY3h67p0syljPk/nClePmQGTPZr0OpVTLpoXqGmlHel6V78vLG49/exn/Xrqb0W8t5teUbPJrWBTlkRHWrOPX59zJ7PQV3OMM5NrxSZoIlFLNTpNBAxhjmL0uhawCJ6/Mt5annDS0W5VjNqVk8+TXm1i7N5PL3lhUUXmy3M7nL2Ns3w7M+Goc76Qv5Vpacde4JH1IrJRyCx0maoBNKdlMmrWG8CA/SssMj17ai4t7R/PGD8ncdUE8PaJDefCTdVU+M/YfSwB47LJenB0Xwf6Da5maNIlvyzIZ4RfJY1d/i+hMYqWUm2gyaIBdh6yhoawCq579hIFxBPr5sP7pRFoF+CIijO3ficz8YlKzCxnx+iLSc4qAUvIdy/nHL++xtGA/DmO4u9053HXZdByO6ovbK6VUc9Fk0ADbj1n2sHw5wrBjCssVlGWwPON7evdbwJ4jqfj7p/P2DiftS0q4xy+aMUNfpH3sec3Wb6WUqo0mg3oqKC5l6sLkiu//O+n8asf8mvErMzbMIGlPEgZDZ0cYA00G7fOLGO4fzaBhz+MTP7Q5u62UUselyaCeFm5No6TM8NJVfbjmrNiKRemNMaw6uIoZG2awOGUxoX4hTIzox5jtS+ic/Rs/lp7J4rZjGXLPJHDoc3ullGfRZFBHB7IKGPCCNbmsTbAfV1dKBPnOfCYvmczc3XOJCIzg/qhBXLf5J1pt+wq6DoGr/4NfcTw3RwRrIlBKeSRNBnX05g9Hh4aG9IisqCe0L2cf9y+8n+TMZO6LGsSErYsJ3DwLYs+DMf+ykgEwyC29VkqputFkUAdzNhzgw2XWGre3DorjgeE9rLkGO2YzZcUUTKmTqbkOBu2cBTFnwcjXoNvFWlNIKeU1NBmcQHJaLr+btYbosAA+vmMAXdoG88uBX5i6dipr09fS1/jx7L49dAmPgxs+gh4jNAkopbxOi0kGztIypszdgrPUMGFgHBv2ZzGyT4cq5aMBsvKdhAT4sH5/Fj9tTeeNH7YTGuDL7PsG8Gvmch7735tsyNpOVJnwTEYGoxxtcCS+CP0n6GIzSimv5bXJIK+45MQHAWVlhqe/2cT7S/dUtJWvU3s4t4irE2IJDfDl05V7mTJvK+m5eYhPLuKbi6/vEeIi99AnNoNrvnqMI6aYTk4nT2VlMyqsJ/7DH4PTxmoSUEp5PTHGuLsPDRIYG2k+nT+HK05NqNK+P7OAf/yYzK5DeYzs05H/LNvN5rT9OAJSuTwB5m1fjSMgFfHNQRxFYPzwFX+cJQ58fPIwPsXVflZEaSnnFTq5OKQzF/W6Ft9el0N43dYtUEopTyIiq4wxCdXavTUZBHUNMt2e7kb38NPwLe5BXpGTUkrYnZENjnzENxuHXxbim4U4jt5FdAjpQKeQU9i234f0bEBKQJzEtvVncHQgHXf/TERga9oGR9E2NIYuUWcQHnsetO0GWjJCKeXlaksGXjtM5FvSkcKDl7GlcDU+gV9ijA8YHwJa+xEZHE64fzvaBMTRLSKWLuExxIfH0zOiJ+EB4YB1B7FubyaLtqczvHc0Q3tptVClVMvltXcGCQkJZtAfp7N0RwZX9Y/hD4k9cYhUTARTSilV3Ul3ZwDw+nV9EX2NUymlGs2rayNoIlBKKdfwmGQgIiNEZKuIJIvII+7uj1JKtSQekQxExAd4C7gU6A3cICK93dsrpZRqOTwiGQDnAMnGmJ3GmGLgI2CUm/uklFIthqckgxhgb6Xv99ltSimlmoGnJIM6EZE7RGSliKxMT093d3eUUuqk4SnJYD8QW+n7TnZbFcaYacaYBGNMQmRkZLN1TimlTnaekgxWAN1FpKuI+APXA7Pd3CellGoxPGLSmTGmRETuA+YBPsA7xphNx/vMqlWrckVkay27w4GserS7Y5+n9acdcKien2vuuLTkeHrS59yxryHx1H3V9wVSWxyNMV75Baw8zr5p9Wl3xz5P64+nxLOhP+9kj6cnfc5b4qn7qu87Xhw9ZZjI1b6pZ7s79rnjZ56oP/X9XHPHpSXH05M+5459x+NJ/fSWfdV4baE6EVlpaii2pBpG4+laGk/X0ni6xvHi6M13BtPc3YGTjMbTtTSerqXxdI1a4+i1dwZKKaVcx5vvDDyOiOSeYP+PIqK3unWk8XQtjadrnWzx1GSglFLK85PBibKvpxGRC0Xk20rf/11EbnFjl6rQeLqWxtO1NJ7u4/HJQCmlVNPzimQgIqEiskBEVovIBhEZZbfHichmEZkuIptEZL6IBLm7v55O4+laGk/X0ni6h1ckA6AQGGOM6Q9cBLwqR9e87A68ZYw5DcgErnJTH8uVUDWuge7qyHFoPF1L4+laGk838JZkIMDzIrIeSMJa6yDa3rfLGLPW3l4FxDV/96rYA/QWkQARaQ0Mc3N/aqLxdC2Np2tpPN3AIwrV1cE4IBI4yxjjFJHdHM3ARZWOKwXcctsoIr5AkTFmr4h8AmwEdgFr3NGfE9B4upbG07U0nm7gLckgHEizfzEuArq4u0M1OA3YAWCMeQh46NgDjDEXNnOfaqPxdC2Np2tpPN3Ao5NBefYFPgC+EZENwEpgi1s7dgwRuQuYBPze3X05Ho2na2k8XUvj6V4eXY5CRM4EphtjznF3X04GGk/X0ni6lsbTvTz2AbKdfWcBT7i7LycDjadraTxdS+Ppfh59Z6CUUqp5eMydgYjEishCEfnVnlByv90eISLfi8h2+982dnsvEVkqIkUi8sdK5+kpImsrfWWLyEk1tlcXroqnve8B+xwbRWSWiHjtu9QN5eJ43m/HclNL/N2EBsVznIisF2sS2hJ7SKn8XCNEZKuIJIvII+66Jq9X2xJozf0FdAD629utgG1Ab2AK8Ijd/gjwkr0dBZwNPAf8sZZz+gCpQBd3X5+3xhPrHe9dQJD9/SfALe6+Pi+O5+lYryEGY73AkQR0c/f1eUE8BwJt7O1LgWX2tg/WWz2nAP7AOqC3u6/PG7885s7AGHPAGLPa3s4BNmP9RzQKeM8+7D1gtH1MmjFmBeA8zmmHATuMMXuarOMeysXx9AWC7Lc9goGUJu6+x3FhPE/F+o8s3xhTAvwEjG2GS/AoDYjnEmPMEbv9F6CTvX0OkGyM2WmMKQY+ss+h6sljkkFlIhIH9AOWAdHGmAP2rlSOzkSsi+uxHkq1aI2JpzFmP/AK8BtwAMgyxsxvss56gUb+fm4EzheRtiISDFwGxDZRV71CA+I5EZhjb8cAeyvt22e3qXryuGQgIqHA58DvjTHZlfcZ676wTk+8RcQfuBL41OWd9CKNjac9ZjsK6Ap0BEJE5KYm6q7Ha2w8jTGbgZeA+cBcYC3WTNoWqb7xtCehTQQebrZOthAelQxExA/rF+MDY8wXdvNBEelg7+8ApNXxdJcCq40xB13fU+/gonhejFUPJt0Y4wS+wBq/bXFc9ftpjHnbGHOWMWYIcARrvLzFqW88ReQMYAYwyhiTYTfvp+qdVSe7TdWTxyQDERHgbWCzMea1SrtmAxPs7QnA13U85Q204CEiF8bzN+A8EQm2zzkMa3y3RXHl76eIRNn/dsZ6XvCha3vr+eobTztWXwDjjTGVk+cKoLuIdLVHA663z6Hqy91PsMu/gMFYt4TrsW6d12KNp7YFFgDbsd68iLCPb481PpiNVcp2HxBm7wsBMoBwd1/XSRLPP2OVBNgI/BsIcPf1eXk8FwG/Yr35Mszd1+Yl8ZyBdRdVfuzKSue6DOvuagfwuLuvzVu/dNKZUkopzxkmUkop5T6aDJRSSmkyUEoppclAKaUUmgyUUkqhyUCpBhGRp4+tRnrM/tEi0rs5+6RUY2gyUKppjMaqwqmUV9B5BkrVkYg8jjUrNg2rONoqIAu4A6t8cjIwHugLfGvvywKusk/xFhAJ5AO3G2M8am1f1bJpMlCqDkTkLGAmcC5WSe/VwD+Bd41dJ0dEngUOGmPeFJGZwLfGmM/sfQuAu4wx20XkXOAFY8zQ5r8SpWrm6+4OKOUlzge+NMbkA4hIef2b0+0k0BoIBeYd+0G7MudA4FOrJA8AAU3eY6XqQZOBUo0zExhtjFknIrcAF9ZwjAPINMb0bcZ+KVUv+gBZqbr5GRgtIkEi0gq4wm5vBRywyzGPq3R8jr0PY9Xp3yUi14BVsbPyGr5KeQJNBkrVgbGWaPwYq9LoHKzSyQBPYq3QtRirsmu5j4A/icgaEYnHShQTRWQdsAldmlF5GH2ArJRSSu8MlFJKaTJQSimFJgOllFJoMlBKKYUmA6WUUmgyUEophSYDpZRSaDJQSikF/D9pC0abtwBCugAAAABJRU5ErkJggg==\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "l0atR1vfvfTS"
      },
      "source": [
        "---------------------"
      ]
    }
  ]
}